code: def _validate_coefficients(coeffs, n_inputs, can_be_list=True):
      """Helper function to validate input coefficients of plotting functions.
  
      Args:
          coeffs (array[complex]): A set (or list of sets) of Fourier coefficients of a
              n_inputs-dimensional function.
          n_inputs (int): The number of inputs (dimension) of the function the coefficients are for.
          can_be_list (bool): Whether or not the plotting function accepts a list of
              coefficients, or only a single set.
  
      Raises:
          TypeError: If the coefficients are not a list or array.
          ValueError: if the coefficients are not a suitable type for the plotting function.
      """
      # Make sure we have a list or numpy array
      if not isinstance(coeffs, list) and not isinstance(
          coeffs, np.ndarray
      ):
          raise TypeError(
              "Input to coefficient plotting functions must be a list of numerical "
              f"Fourier coefficients. Received input of type {type(coeffs)}"
          )
  
      # In case we have a list, turn it into a numpy array
      if isinstance(coeffs, list):
          coeffs = np.array(coeffs)
  
      # Check if the user provided a single set of coefficients to a function that is
      # meant to accept multiple samples; add an extra dimension around it if needed
      if len(coeffs.shape) == n_inputs and can_be_list:
          coeffs = np.array([coeffs])
  
      # Check now that we have the right number of axes for the type of function
      required_shape_size = n_inputs + 1 if can_be_list else n_inputs
      if len(coeffs.shape) != required_shape_size:
          raise ValueError(
              f"Plotting function expected a list of {n_inputs}-dimensional inputs. "
              f"Received coefficients of {len(coeffs.shape)}-dimensional function."
          )
  
      # Size of each sample dimension must be 2d_i + 1 where d_i is the i-th degree
      dims = coeffs.shape[1:] if can_be_list else coeffs.shape
      if any((dim - 1) % 2 for dim in dims):
          raise ValueError(
              "Shape of input coefficients must be 2d_i + 1, where d_i is the largest frequency "
              f"in the i-th input. Coefficient array with shape {coeffs.shape} is invalid."
          )
  
      # Return the coefficients; we may have switched to a numpy array or added a needed extra dimension
      return coeffs
  
file_path: pennylane/pennylane/fourier/visualize.py
imports: from itertools import product
  import numpy
  from .utils import format_nvec
label_desc: Use image node_id 1 for calling a global function with example usage: _validate_coefficients(coeffs, n_inputs, can_be_list) and returns: coeffs